Ambulances and emergency vehicles (buses and taxis as well) if equipped with wireless devices, can be exploited to harvest medical data during unexpected events and also on a daily basis, from all those patients that require a constant monitoring of health conditions. Ambulances can be utilized as trusted intermediaries to transport medical information, at little cost, to hospital central servers. Patients equipped with physiological sensors connected to wireless devices could dump, during each contact, all the medical information collected so far, thus utilizing emergency vehicles as data mules. Inevitably, contact times may be short and not sufficient to transfer all of the information collected from a patient’s medical sensors. In such cases, computing in advance, or during the very initial phase of a data transfer, an estimate of how long a contact time will last is key to maximize the utility of any successfully transmitted chunks, in general of different sizes and priorities, of medical data. In this paper we address the problem of predicting patient-vehicle contact times, through an empirical model based on real-world experiments focused on the key sections of a road, which most influence the average speed of an emergency vehicle that traverses it. Our preliminary results are encouraging, as they indicate that it is possible to predict the time an emergency vehicle will spend traversing a given road segment within one third of its traversal.

Efficient Vehicle-To-Pedestrian Exchange of Medical Data: An Empirical Model with Preliminary Results

MARFIA, GUSTAVO;ROCCETTI, MARCO;AMOROSO, ALESSANDRO
2011

Abstract

Ambulances and emergency vehicles (buses and taxis as well) if equipped with wireless devices, can be exploited to harvest medical data during unexpected events and also on a daily basis, from all those patients that require a constant monitoring of health conditions. Ambulances can be utilized as trusted intermediaries to transport medical information, at little cost, to hospital central servers. Patients equipped with physiological sensors connected to wireless devices could dump, during each contact, all the medical information collected so far, thus utilizing emergency vehicles as data mules. Inevitably, contact times may be short and not sufficient to transfer all of the information collected from a patient’s medical sensors. In such cases, computing in advance, or during the very initial phase of a data transfer, an estimate of how long a contact time will last is key to maximize the utility of any successfully transmitted chunks, in general of different sizes and priorities, of medical data. In this paper we address the problem of predicting patient-vehicle contact times, through an empirical model based on real-world experiments focused on the key sections of a road, which most influence the average speed of an emergency vehicle that traverses it. Our preliminary results are encouraging, as they indicate that it is possible to predict the time an emergency vehicle will spend traversing a given road segment within one third of its traversal.
Proceedings of 1st ACM International Workshop on Pervasive Wireless Healthcare - 12th ACM International Symposium on Mobile Ad Hoc Networking and Computing
5
8
G. Marfia; M. Roccetti; C. E. Palazzi; A. Amoroso
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/102282
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